» Articles » PMID: 22809148

Automated Vs Manual Delineations of Regions of Interest- a Comparison in Commercially Available Perfusion MRI Software

Overview
Journal BMC Med Imaging
Publisher Biomed Central
Specialty Radiology
Date 2012 Jul 20
PMID 22809148
Citations 3
Authors
Affiliations
Soon will be listed here.
Abstract

Background: In perfusion magnetic resonance imaging a manual approach to delineation of regions of interest is, due to rater bias and time intensive operator input, clinically less favorable than an automated approach would be. The goal of our study was to compare the performances of these approaches.

Methods: Using Stroketool, PMA and Perfscape/Neuroscape perfusion maps of cerebral blood flow, mean transit time and Tmax were created for 145 patients with acute ischemic stroke. Volumes of hypoperfused tissue were calculated using both a manual and an automated protocol, and the results compared between methods.

Results: The median difference between the automatically and manually derived volumes was up to 210 ml in Perfscape/Neuroscape, 123 ml in PMA and 135 ml in Stroketool. Correlation coefficients between perfusion volumes and radiological and clinical outcome were much lower for the automatic volumes than for the manually derived ones.

Conclusions: The agreement of the two methods was very poor, with the automated use producing falsely exaggerated volumes of hypoperfused tissue. Software improvements are necessary to enable highly automated protocols to credibly assess perfusion deficits.

Citing Articles

Image-to-image generative adversarial networks for synthesizing perfusion parameter maps from DSC-MR images in cerebrovascular disease.

Kossen T, Madai V, Mutke M, Hennemuth A, Hildebrand K, Behland J Front Neurol. 2023; 13:1051397.

PMID: 36703627 PMC: 9871486. DOI: 10.3389/fneur.2022.1051397.


Assessing reperfusion with whole-brain arterial spin labeling: a noninvasive alternative to gadolinium.

Mirasol R, Bokkers R, Hernandez D, Merino J, Luby M, Warach S Stroke. 2014; 45(2):456-61.

PMID: 24385278 PMC: 4279920. DOI: 10.1161/STROKEAHA.113.004001.


Diffusion- and perfusion-weighted imaging in acute lacunar infarction: is there a mismatch?.

Forster A, Kerl H, Wenz H, Brockmann M, Nolte I, Groden C PLoS One. 2013; 8(10):e77428.

PMID: 24130885 PMC: 3795042. DOI: 10.1371/journal.pone.0077428.

References
1.
Kosior R, Kosior J, Frayne R . Improved dynamic susceptibility contrast (DSC)-MR perfusion estimates by motion correction. J Magn Reson Imaging. 2007; 26(4):1167-72. DOI: 10.1002/jmri.21128. View

2.
Galinovic I, Brunecker P, Ostwaldt A, Soemmer C, Hotter B, Fiebach J . Fully automated postprocessing carries a risk of substantial overestimation of perfusion deficits in acute stroke magnetic resonance imaging. Cerebrovasc Dis. 2011; 31(4):408-13. DOI: 10.1159/000323212. View

3.
Yamada K, Wu O, Gonzalez R, Bakker D, Ostergaard L, Copen W . Magnetic resonance perfusion-weighted imaging of acute cerebral infarction: effect of the calculation methods and underlying vasculopathy. Stroke. 2002; 33(1):87-94. DOI: 10.1161/hs0102.101893. View

4.
Kim J, Leira E, Callison R, Ludwig B, Moritani T, Magnotta V . Toward fully automated processing of dynamic susceptibility contrast perfusion MRI for acute ischemic cerebral stroke. Comput Methods Programs Biomed. 2010; 98(2):204-13. DOI: 10.1016/j.cmpb.2009.12.005. View

5.
Olivot J, Mlynash M, Thijs V, Kemp S, Lansberg M, Wechsler L . Optimal Tmax threshold for predicting penumbral tissue in acute stroke. Stroke. 2008; 40(2):469-75. PMC: 2670783. DOI: 10.1161/STROKEAHA.108.526954. View